first commit

app.py

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+import streamlit as st
+import requests
+import pandas as pd
+
+# Set FastAPI backend URL
+API_URL = "http://127.0.0.1:8000"  # Change this if deployed elsewhere
+
+# Streamlit UI
+st.set_page_config(page_title="Loan Risk Analysis Dashboard", layout="wide")
+
+st.title("📊 Loan Risk Analysis Dashboard")
+
+# Sidebar for Navigation
+st.sidebar.header("Navigation")
+page = st.sidebar.radio(
+    "Go to",
+    [
+        "Loan Status Distribution",
+        "Payment Timeline Analysis",
+        "Principal Amount Patterns",
+        "Credit History Impact",
+        "Customer Profile Analysis",
+        "Loan Intent Analysis",
+        "Collection Effectiveness",
+        "Risk Score Development"
+    ],
+)
+
+# Function to fetch data from FastAPI backend
+def fetch_data(endpoint):
+    try:
+        response = requests.get(f"{API_URL}/{endpoint}")
+        if response.status_code == 200:
+            return response.json()
+        else:
+            st.error(f"Error fetching data: {response.json()['detail']}")
+            return None
+    except requests.exceptions.RequestException as e:
+        st.error(f"API request failed: {e}")
+        return None
+
+# Loan Status Distribution
+if page == "Loan Status Distribution":
+    st.subheader("📌 Loan Status Distribution")
+    data = fetch_data("loan_status_distribution")
+    if data:
+        st.write(data)
+        st.bar_chart(pd.DataFrame([data], index=["Loan Status"]).T)
+
+# Payment Timeline Analysis
+elif page == "Payment Timeline Analysis":
+    st.subheader("📌 Payment Timeline Analysis")
+    data = fetch_data("payment_timeline_analysis")
+    if data:
+        st.write(data)
+        st.bar_chart(pd.DataFrame(data["average_loan_amount_by_status"], index=["Loan Amount"]).T)
+
+# Principal Amount Patterns
+elif page == "Principal Amount Patterns":
+    st.subheader("📌 Principal Amount Patterns")
+    data = fetch_data("principal_amount_patterns")
+    if data:
+        df = pd.DataFrame(data)
+        st.write(df)
+        st.bar_chart(df.set_index("loan_status")["count"])
+
+# Credit History Impact
+elif page == "Credit History Impact":
+    st.subheader("📌 Credit History Impact")
+    data = fetch_data("credit_history_impact")
+    if data:
+        st.write(data)
+
+# Customer Profile Analysis
+elif page == "Customer Profile Analysis":
+    st.subheader("📌 Customer Profile Analysis")
+    data = fetch_data("customer_profile_analysis")
+    if data:
+        df = pd.DataFrame(data["customer_profile_analysis"])
+        st.write(df)
+        st.bar_chart(df.set_index("person_age")["success_rate"])
+
+# Loan Intent Analysis
+elif page == "Loan Intent Analysis":
+    st.subheader("📌 Loan Intent Analysis")
+    data = fetch_data("loan_intent_analysis")
+    if data:
+        st.write(data)
+
+# Collection Effectiveness
+elif page == "Collection Effectiveness":
+    st.subheader("📌 Collection Effectiveness")
+    data = fetch_data("collection_effectiveness")
+    if data:
+        st.write(data)
+
+# Risk Score Development
+elif page == "Risk Score Development":
+    st.subheader("📌 Risk Score Development")
+    data = fetch_data("risk_score_development")
+    if data:
+        st.write(data)
+        st.bar_chart(pd.DataFrame(data, index=["Risk Score"]).T)
+
+# Run Streamlit
+st.sidebar.info("📢 Select an option from the navigation to analyze loan risk insights.")